• Geomechanics and Engineering
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• 제6권2호
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• pp.99-115
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• 2014

Uncertainties in design variables and design equations have a significant impact on the safety of geotechnical structures like retaining walls and slopes. This paper presents a possible framework for obtaining the partial safety factors based on reliability approach for different random variables affecting the stability of a reinforced concrete cantilever retaining wall and a slope under static loading conditions. Reliability analysis is carried out by Mean First Order Second Moment Method, Point Estimate Method, Monte Carlo Simulation and Response Surface Methodology. A target reliability index ${\beta}$ = 3 is set and partial safety factors for each random variable are calculated based on different coefficient of variations of the random variables. The study shows that although deterministic analysis reveals a safety factor greater than 1.5 which is considered to be safe in conventional approach, reliability analysis indicates quite high failure probability due to variation of soil properties. The results also reveal that a higher factor of safety is required for internal friction angle ${\varphi}$, while almost negligible values of safety factors are required for soil unit weight ${\gamma}$ in case of cantilever retaining wall and soil unit weight ${\gamma}$ and cohesion c in case of slope. Importance of partial safety factors is shown by analyzing two simple geotechnical structures. However, it can be applied for any complex system to achieve economization.

• Geomechanics and Engineering
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• 제18권6호
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• pp.595-603
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• 2019

A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.

• 대한조선학회논문집
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• 제57권5호
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• pp.297-304
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• 2020

In this study, the prediction method was reviewed to process a cylindrical plate forming using machine learning as a data-driven approach by roll bending equipment. The calculation of the forming variables was based on the analysis using the mechanical relationship between the material properties and the roll bending machine in the bending process. Then, by applying the finite element analysis method, the accuracy of the deformation prediction model was reviewed, and a large number data set was created to apply to machine learning using the finite element analysis model for deformation prediction. As a result of the application of the machine learning model, it was confirmed that the calculation is slightly higher than the linear regression method. Applicable results were confirmed through the machine learning method.

• 산업융합연구
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• 제21권1호
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• pp.159-165
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• 2023

최근 지진 발생 빈도가 증가하고 있는 반면 국내 지진 대응 체계는 취약한 현실에서, 본 연구의 목적은 통계분석 기법과 머신러닝 기법을 활용한 공간분석을 통해 건물의 지진취약도를 비교분석 하는 것이다. 통계분석 기법을 활용한 결과, 최적화척도법을 활용해 개발된 모델의 예측정확도는 약 87%로 도출되었다. 머신러닝 기법을 활용한 결과, 분석된 4가지 방법 중, Random Forest의 정확도가 Train Set의 경우 94%, Test Set의 경우 76.7%로 가장 높아, 최종적으로 Random Forest가 선정되었다. 따라서, 예측정확도는 통계분석 기법이 약 87%, 머신러닝 기법이 76.7%로, 통계분석 기법의 예측정확도가 더 높은 것으로 분석되었다. 최종 결과로, 건물의 지진취약도는 분석된 건물데이터 총 22,296개 중, 1,627(0.1%)개의 건물데이터는 통계분석 기법 사용 시 더 위험하다고 도출되었고, 10,146(49%)개의 건물데이터는 동일하게 도출되었으며, 나머지 10,523(50%)개의 건물데이터는 머신러닝 기법 사용 시 더 위험하게 도출되었다. 기존 통계분석 기법에 첨단 머신러닝 기법활용결과가 추가로 비교검토 됨으로써 공간분석 의사결정에 있어서, 좀더 신뢰도가 높은 지진대응책 마련에 도움이 되길 기대한다.

• 한국정보전자통신기술학회논문지
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• 제8권4호
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• pp.263-269
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• 2015

디지털 워터마킹은 인간의 감각으로 감지할 수 없고 통계적인 방법에 의하여 검출되지 않는 정보를 디지털 데이터에 삽입하는 기술이다. 일반적으로 디지털 음향 신호에 대한 워터마킹은 의미 있는 정보를 갖는 이진 시퀀스를 원래의 디지털 음향 신호에 삽입하여 구현한다. 그러나 삽입된 이진 정보는 원래의 디지털 음향 신호의 관점에서는 잡음으로 작용하여 원래의 음향 신호를 왜곡 시키거나 열화 시키는 원인으로 작용한다. 본 논문에서는 인간의 가청 주파수 영역에서 이진 정보의 삽입으로 인한 원 음향 정보의 왜곡을 최소화시킬 수 있는 이진 정보 발생 방법을 제안하였다. 제안한 방법은 표준부호 디지트 코딩을 이용한 방법으로서 인접한 데이터간의 주파수 간섭을 최소화 하여 인간의 가청 주파수 영역에서의 이진 정보 시퀀스의 영향을 최소화 하도록 구현하였다. 제안한 방법은 일반적인 이진 정보발생 방법과 주파수 분석 비교를 통하여 성능을 평가하였다.

• Structural Engineering and Mechanics
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• 제28권2호
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• pp.129-152
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• 2008

This paper considers the solution of the stochastic differential equations (SDEs) with random operator and/or random excitation using the spectral SFEM. The random system parameters (involved in the operator) and the random excitations are modeled as second order stochastic processes defined only by their means and covariance functions. All random fields dealt with in this paper are continuous and do not have known explicit forms dependent on the spatial dimension. This fact makes the usage of the finite element (FE) analysis be difficult. Relying on the spectral properties of the covariance function, the Karhunen-Loeve expansion is used to represent these processes to overcome this difficulty. Then, a spectral approximation for the stochastic response (solution) of the SDE is obtained based on the implementation of the concept of generalized inverse defined by the Neumann expansion. This leads to an explicit expression for the solution process as a multivariate polynomial functional of a set of uncorrelated random variables that enables us to compute the statistical moments of the solution vector. To check the validity of this method, two applications are introduced which are, randomly loaded simply supported reinforced concrete beam and reinforced concrete cantilever beam with random bending rigidity. Finally, a more general application, randomly loaded simply supported reinforced concrete beam with random bending rigidity, is presented to illustrate the method.

• 한국ITS학회 논문지
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• 제16권1호
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• pp.26-37
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• 2017

본 연구는 random effects Tobit 회귀모형을 이용하여 도심지 교차로에 대한 교통사고모형을 개발하여 교통사고와 요인간의 상관관계를 파악하는 것이 목적이다. Random effects Tobit 회귀모형의 적용성을 비교 분석하기 위하여 fixed effect Tobit 회귀모형을 산정하였다. 산정결과, 교통량, 제한속도, 차로수, 토지이용, 우회전차로, 전방신호등이 유효한 변수로 나타났으며, 총 교통사고율에 대한 random effects 모형의 모형 적합도(결정계수: 0.418, 로그-우도함수값: -3210.103, 우도비: 0.056)와 모형 설명력(MAD: 19.533, MAPE: 75.725, RMSE: 26.886)은 fixed effects 모형의 모형 적합도 (결정계수: 0.298, 로그-우도함수값: -3276.138, 우도비: 0.037)와 모형 설명력(MAD: 20.725, MAPE: 82.473, RMSE: 27.267)보다 우수한 것으로 나타났으며, 부상교통사고율에 대한 교통사고모형에서도 총 교통사고율의 산정결과와 동일하게 나타나 두 모형에서 random effects Tobit 회귀모형이 다소 우수한 것으로 분석되었다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 2000년도 하계학술발표대회 논문집 제19권 1호
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• pp.283-286
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• 2000

흡음률을 예측 및 평가하기 위한 연구로서 우선 수직입사 흡음률을 예측하는 경험식 모델에 대한 비교 연구를 수행하였다. 비교결과는 Voronina 가 제안한 경험식이 상대적으로 실험치와 잘 일치하고 있다. 한편 수직입사와 랜덤입사와의 상관관계를 실험 연구를 통하여 조사하였다. 이 상관관계는 주파수에 따라서 다르게 나타나고 있다. 저주파수 대역에서는 랜덤 입사가 수직입사 보다 크게 나타나고 있지만 고주파수에서는 수평입사 성분의 영향으로 랜덤입사에서는 감소하는 경향을 보이고 있다.

• 천문학회보
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• 제38권2호
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• pp.56.2-56.2
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• 2013

We study the three-dimensional genus topology of large-scale structure using the CMASS Data Release 11 sample of the SDSS-III Baryon Oscillation Spectroscopic Survey (BOSS). The CMASS sample yields a genus curve that is characteristic of one produced by Gaussian random-phase initial conditions. The data thus supports the standard model of inflation where random quantum fluctuations in the early universe produced Gaussian random-phase initial conditions. Modest deviations in the observed genus from random phase are as expected from the nonlinear evolution of structure. We construct mock SDSS CMASS surveys along the past light cone from the Horizon Run 3 (HR3) N-body simulations, where gravitationally bound dark matter subhalos are identified as the sites of galaxy formation. We study the genus topology of the HR3 mock surveys with the same geometry and sampling density as the observational sample, and the observed genus topology to be consistent with LCDM as simulated by the HR3 mock samples.

• Journal of Mechanical Science and Technology
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• 제14권9호
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• pp.968-977
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• 2000

The motion of an aircraft landing gear over a rough runway can be modeled by a nonclassically damped system subject to nonstationary random excitations. In this paper, the approximate analysis methods based on either the real or complex normal modes for the computation of nonstationary response covariances are proposed. It has been found by simulation involving a realistic example that, for the nonclassically damped random vibrational systems, the approximate solution method based on the complex normal mode is superior to other approaches with respect to the accuracy and computation time.